A Comparative Study of Scalable Data Warehousing Frameworks for Real-Time Big Data Mining in Cloud-Based Environments
Abstract
The exponential growth of big data, particularly in cloud environments, has demanded scalable, real-time data warehousing frameworks that can efficiently support mining operations. This study compares leading frameworks—including Amazon Redshift, Google BigQuery, Snowflake, and Apache Hive—based on performance, scalability, cost, and integration capabilities. Real-time mining efficiency and cloud-native optimization are the focal metrics. Results highlight a performance-cost trade-off between commercial and open-source solutions and propose future optimizations for hybrid architectures
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